Healthcare IT leaders walked into 2026 facing a familiar tension: the pressure to modernize faster than ever, against infrastructure and workflows that were never built for the pace being asked of them. Four forces are driving that tension right now: AI adoption in clinical workflows, interoperability, cybersecurity, and legacy modernization. And they’re deeply connected: solve one in isolation and the other three usually push back.
Here’s where each stands today:
AI in the clinical workflow, if the data can support it
Every health system conversation eventually turns to AI: ambient documentation, prior authorization automation, diagnostic support, and clinical decision tools. AI want is real. The readiness, less so. Across industries, roughly three-quarters of procurement and data leaders say their organization’s data isn’t actually AI-ready; it’s siloed, inconsistently labeled, or locked in legacy formats that models can’t reliably use. Healthcare feels this acutely, because clinical data lives across EHRs, imaging systems, lab platforms, and decades-old point solutions that were never designed to talk to each other.
The fix isn’t a model; it’s the data foundation underneath it: breaking down silos with data lakes and ETL pipelines, standardizing metadata and taxonomies, and building in governance and access controls from the start rather than bolting them on later. That groundwork is unglamorous, but it’s what determines whether an AI pilot actually scales past a proof of concept or stalls out because the underlying data can’t support it in production.
Interoperability is finally becoming operational, not aspirational
FHIR (Fast Healthcare Interoperability Resources) has become a standard everyone is actually building on. REST APIs, HTTP, and JSON-based exchanges are replacing batch file transfers and manual reconciliation that used to define how EHRs shared data, a shift that matters directly for AI and analytics initiatives, since neither works well with fragmented records.
This is where ClearBridge has spent a lot of its recent healthcare IT work. On one engagement, a government health agency brought in ClearBridge Mirth Integration Engineers to support a broader system modernization effort, building out health information exchanges using HL7, FHIR, REST services, and JSON-formatted data so disparate systems could exchange records in real time rather than through manual, point-to-point handoffs. The value wasn’t a single integration; it was building the connective tissue that let previously siloed stakeholders make faster, better-informed decisions as requirements kept shifting.
Cybersecurity: the threat isn’t slowing down, but the posture is maturing
The numbers are still sobering. Healthcare organizations reported roughly 789 large data breaches in 2025, affecting an estimated 138.5 million people, and hacking or other IT-related incidents accounted for more than 80% of those breaches. Early 2026 figures show breach counts running about 9.5% below the same period last year, a hopeful sign, though reporting delays make it too early to call a real trend reversal. Recent mega-breaches have made clear that a single point of failure in a connected health ecosystem can cascade across millions of patients almost instantly.
That’s the uncomfortable flip side of interoperability: every new API, every new data-sharing connection, is also a new attack surface. Health IT teams are responding by pairing integration work with information security architecture and governance rather than treating them as separate workstreams — building access controls, anonymization, and monitoring into the exchange layer itself, not as an afterthought.
Modernization: the infrastructure has to catch up
None of the above works on top of infrastructure that’s still running on aging, on-premises platforms. Health systems are steadily shifting EHR, clinical application, and revenue-cycle workloads to cloud environments and modern virtualization platforms, both to support real-time interoperability and to provide AI and analytics tools with the compute and access patterns they actually need. It’s rarely a clean rip-and-replace; it’s staged migrations, careful workflow and gap analysis, and change management to bring clinical and revenue-cycle staff along, since a modernization effort that ignores adoption tends to stall regardless of how sound the technical architecture is.
The throughline
AI, interoperability, cybersecurity, and modernization aren’t four separate initiatives competing for budget; they’re four faces of the same underlying challenge: building a health IT environment where data can move safely, quickly, and accurately to wherever it’s needed next. Organizations that treat them together, starting with clean, governed, interoperable data, are the ones best positioned to actually put AI and modern infrastructure to work, rather than being stuck in pilot mode.
ClearBridge has spent more than two decades working alongside health systems, government health agencies, and payers on exactly this kind of work, from FHIR-based health information exchanges to platform modernization under real-world regulatory and operational pressure. If your organization is navigating any one of these four forces, it’s worth having a conversation about the other three.
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